May 2022 arXiv papers — page 3

Takuya Kawata, Takahiro Tsukahara

In recent years, scale-by-scale energy transport in wall turbulence has been intensively studied, and the complex spatial and interscale transfer of turbulent energy has been investigated. As the enhancement of heat transfer is one of the most important aspects of turbulence from an engineering perspective, it is also important to study how turbulent heat fl

Junlin Han, Lars Petersson, Hongdong Li, Ian Reid

We present a simple method, CropMix, for the purpose of producing a rich input distribution from the original dataset distribution. Unlike single random cropping, which may inadvertently capture only limited information, or irrelevant information, like pure background, unrelated objects, etc, we crop an image multiple times using distinct crop scales, thereb

Yijun Yuan, Andreas Nuechter

In recent years, implicit functions have drawn attention in the field of 3D reconstruction and have successfully been applied with Deep Learning. However, for incremental reconstruction, implicit function-based registrations have been rarely explored. Inspired by the high precision of deep learning global feature registration, we propose to combine this with

David Mguni, Aivar Sootla, Juliusz Ziomek, Oliver Slumbers

Many real-world settings involve costs for performing actions; transaction costs in financial systems and fuel costs being common examples. In these settings, performing actions at each time step quickly accumulates costs leading to vastly suboptimal outcomes. Additionally, repeatedly acting produces wear and tear and ultimately, damage. Determining \textit{

Ankush Agarwal, Raj Gite, Shreya Laddha, Pushpak Bhattacharyya

In the commercial aviation domain, there are a large number of documents, like, accident reports (NTSB, ASRS) and regulatory directives (ADs). There is a need for a system to access these diverse repositories efficiently in order to service needs in the aviation industry, like maintenance, compliance, and safety. In this paper, we propose a Knowledge Graph (

Sandhya Singh, Prapti Roy, Nihar Sahoo, Niteesh Mallela

Movies reflect society and also hold power to transform opinions. Social biases and stereotypes present in movies can cause extensive damage due to their reach. These biases are not always found to be the need of storyline but can creep in as the author's bias. Movie production houses would prefer to ascertain that the bias present in a script is the story's

Sebastian Schuster, Jessica Santiago, Matt Visser

What happens when a warp bubble has mass? This seemingly innocent question forces one to carefully formalize exactly what one means by a warp bubble, exactly what one means by having the warp bubble "move" with respect to the fixed stars, and forces one to more carefully examine the notion of mass in warp-drive spacetimes. This is the goal of the present art

Alexander Golovanov

L\'{a}szl\'{o} Fejes T\'{o}th and Alad\'{a}r Heppes proposed the following generalization of the kissing number problem. Given a ball in $\mathbb{R}^d$, consider a family of balls touching it, and another family of balls touching the first family. Find the maximal possible number of balls in this arrangement, provided that no two balls intersect by interiors

Paresh Kumar Panigrahi, Sukanta Nayak, Sudipta Priyadarshini

This paper investigates fuzzy nonlinear system equations using an optimization approach. Here, the inner-outer direct search technique is used with fuzzy coefficients and vectors to quantify the uncertain solution. The fuzzy nonlinear system of equations is converted into an unconstrained fuzzy multivariable optimization problem with preserving the operating

Xuan Bac Nguyen, Apoorva Bisht, Ben Thompson, Hugh Churchill

In quantum machine field, detecting two-dimensional (2D) materials in Silicon chips is one of the most critical problems. Instance segmentation can be considered as a potential approach to solve this problem. However, similar to other deep learning methods, the instance segmentation requires a large scale training dataset and high quality annotation in order

Ruchit Agrawal

Music can be represented in multiple forms, such as in the audio form as a recording of a performance, in the symbolic form as a computer readable score, or in the image form as a scan of the sheet music. Music synchronisation provides a way to navigate among multiple representations of music in a unified manner by generating an accurate mapping between them

Nikolaj Thams, Michael Oberst, David Sontag

We give a method for proactively identifying small, plausible shifts in distribution which lead to large differences in model performance. These shifts are defined via parametric changes in the causal mechanisms of observed variables, where constraints on parameters yield a "robustness set" of plausible distributions and a corresponding worst-case loss over

Naser Ahmadiniaz, Alexander M. Fedotov, Evgeny G. Gelfer, Sang Pyo Kim

In previous work on Schwinger pair creation in purely time-dependent fields, it was shown how to construct ``solitonic'' electric fields that do not create scalar pairs with an arbitrary fixed momentum. We show that this construction can be adapted to the fermionic case in two inequivalent ways, both closely related to supersymmetric quantum mechanics for re

Naser Ahmadiniaz, Sang Pyo Kim, Christian Schubert

Schwinger pair creation in a purely time-dependent electric field can be reduced to an effective quantum mechanical problem using a variety of formalisms. Here we develop an approach based on the Gelfand-Dikii equation for scalar QED, and on a generalization of that equation for spinor QED. We discuss a number of solvable special cases from this point of vie

Zeyan Liu, Fengjun Li, Jingqiang Lin, Zhu Li

With the growing popularity of artificial intelligence and machine learning, a wide spectrum of attacks against deep learning models have been proposed in the literature. Both the evasion attacks and the poisoning attacks attempt to utilize adversarially altered samples to fool the victim model to misclassify the adversarial sample. While such attacks claim

Cameron Ballard, Ian Goldstein, Pulak Mehta, Genesis Smothers

Conspiracy theories are increasingly a subject of research interest as society grapples with their rapid growth in areas such as politics or public health. Previous work has established YouTube as one of the most popular sites for people to host and discuss different theories. In this paper, we present an analysis of monetization methods of conspiracy theori

Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano

The statistical characteristics of instance-label pairs often change with time in practical scenarios of supervised classification. Conventional learning techniques adapt to such concept drift accounting for a scalar rate of change by means of a carefully chosen learning rate, forgetting factor, or window size. However, the time changes in common scenarios a

Yuan Wang, Laura Blackie, Irene Miguel-Aliaga, Wenjia Bai

In recent years, 3D convolutional neural networks have become the dominant approach for volumetric medical image segmentation. However, compared to their 2D counterparts, 3D networks introduce substantially more training parameters and higher requirement for the GPU memory. This has become a major limiting factor for designing and training 3D networks for hi

Jianxin Wang, José Bento

The asymptotic mean squared test error and sensitivity of the Random Features Regression model (RFR) have been recently studied. We build on this work and identify in closed-form the family of Activation Functions (AFs) that minimize a combination of the test error and sensitivity of the RFR under different notions of functional parsimony. We find scenarios

Babu Ram Sankhi, Elena Echeverria, Hans T. Nembach, Justin M. Shaw

The interfacial Dyzaloshinskii-Moria interaction (DMI) helps to stabilize chiral domain walls and magnetic skyrmions, which will facilitate new magnetic memories and spintronics logic devices. The study of interfacial DMI in perpendicularly magnetized structurally asymmetric heavy metal (HM) / ferromagnetic (FM) multilayer systems is of high importance due t

Zhen Li, N. A. Smirnova, A. M. Shirokov, I. J. Shin

In recent years, remarkable progress has been achieved in developing novel non-perturbative techniques for constructing valence space shell model Hamiltonians from realistic internucleon interactions. One of these methods is based on the Okubo--Lee--Suzuki (OLS) unitary transformation applied to no-core shell model (NCSM) solutions. In the present work, we i

Yanwei Li, Xiaojuan Qi, Yukang Chen, Liwei Wang

In this work, we present a conceptually simple yet effective framework for cross-modality 3D object detection, named voxel field fusion. The proposed approach aims to maintain cross-modality consistency by representing and fusing augmented image features as a ray in the voxel field. To this end, the learnable sampler is first designed to sample vital feature

Shengqin Wang, Yongji Zhang, Minghao Zhao, Hong Qi

Skeleton-based action recognition methods are limited by the semantic extraction of spatio-temporal skeletal maps. However, current methods have difficulty in effectively combining features from both temporal and spatial graph dimensions and tend to be thick on one side and thin on the other. In this paper, we propose a Temporal-Channel Aggregation Graph Con

Stefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh, Luca Saglietti

Machine learning (ML) may be oblivious to human bias but it is not immune to its perpetuation. Marginalisation and iniquitous group representation are often traceable in the very data used for training, and may be reflected or even enhanced by the learning models. In the present work, we aim at clarifying the role played by data geometry in the emergence of

Fei Shen, Zhe Wang, Zijun Wang, Xiaode Fu

Vision-based pattern identification (such as face, fingerprint, iris etc.) has been successfully applied in human biometrics for a long history. However, dog nose-print authentication is a challenging problem since the lack of a large amount of labeled data. For that, this paper presents our proposed methods for dog nose-print authentication (Re-ID) task in

Kathleen Yang, Diana C. Gonzalez, Yonina C. Eldar, Muriel Medard

There is a growing interest in signaling schemes that operate in the wideband regime due to the crowded frequency spectrum. However, a downside of the wideband regime is that obtaining channel state information is costly, and the capacity of previously used modulation schemes such as code division multiple access and orthogonal frequency division multiplexin

Shao-Yuan Chen, Li-Xian Zhong, Rui-Xi Zhu, Lian-Sheng Yang

A model is proposed to estimate the work zone queue length, and the cellular automata based on empirical data is used for model validation. This estimation model can be applied to work zone organization and management to improve work zone capacity and security. Relationship between the average queue length and the warning zone length can be found, and the ap

David Aldous, Alice Contat, Nicolas Curien, Olivier Hénard

Let $(A_u : u \in \mathbb{B})$ be i.i.d.~non-negative integers that we interpret as car arrivals on the vertices of the full binary tree $ \mathbb{B}$. Each car tries to park on its arrival node, but if it is already occupied, it drives towards the root and parks on the first available spot. It is known that the parking process on $ \mathbb{B}$ exhibits a ph

Ryan Boldi, Thomas Helmuth, Lee Spector

Down-sampling training data has long been shown to improve the generalization performance of a wide range of machine learning systems. Recently, down-sampling has proved effective in genetic programming (GP) runs that utilize the lexicase parent selection technique. Although this down-sampling procedure has been shown to significantly improve performance acr

Sanatbek Matlatipov, Hulkar Rahimboeva, Jaloliddin Rajabov, Elmurod Kuriyozov

Extracting useful information for sentiment analysis and classification problems from a big amount of user-generated feedback, such as restaurant reviews, is a crucial task of natural language processing, which is not only for customer satisfaction where it can give personalized services, but can also influence the further development of a company. In this p

Richard J. Boucherie

This paper considers the cycle maximum in birth-death processes as a stepping stone to characterisation of the cycle maximum in single queues and open Kelly-Whittle networks of queues. For positive recurrent birth-death processes we show that the sequence of sample maxima is stochastically compact. For transient birth-death processes we show that the sequenc

J. P. Carlomagno, D. Gomez Dumm, S. Noguera, N. N. Scoccola

Mixing effects on the mass spectrum of light neutral pseudoscalar and vector mesons in the presence of an external uniform magnetic field $\vec B$ are studied in the framework of a two-flavor NJL-like model. The model includes isoscalar and isovector couplings both in the scalar-pseudoscalar and vector sectors, and also incorporates flavor mixing through a '

Yong Hu, Xianxin Wu, Yongqi Yang, Shunye Gao

Transition-metal-based kagome materials at van Hove filling are a rich frontier for the investigation of novel topological electronic states and correlated phenomena. To date, in the idealized two-dimensional kagome lattice, topologically nontrivial Dirac surface states (TDSSs) have not been unambiguously observed, and the manipulation of TDSSs and van Hove

Florian Jörg, Guillaume Eurin, Hardy Simgen

Precise radon measurements are a requirement for various applications, ranging from radiation protection over environmental studies to material screening campaigns for rare-event searches. All of them ultimately depend on the availability of calibration sources with a known and stable radon emanation rate. A new approach to produce clean and dry radon source

Robert T. W. Martin

Let $A$ be a bounded, injective and self-adjoint linear operator on a complex separable Hilbert space. We prove that there is a pure isometry, $V$, so that $AV>0$ and $A$ is Hankel with respect to $V$, i.e. $V^*A = AV$, if and only if $A$ is not invertible. The isometry $V$ can be chosen to be isomorphic to $N \in \mathbb{N} \cup \{ + \infty \}$ copies of th

Jin Guo, Zhen Han, Zhou Su, Jiliang Li

There has been an increasing interest in modeling continuous-time dynamics of temporal graph data. Previous methods encode time-evolving relational information into a low-dimensional representation by specifying discrete layers of neural networks, while real-world dynamic graphs often vary continuously over time. Hence, we propose Continuous Temporal Graph N

G. Claussen, A. K. Hartmann

The phase-transition behavior of the NP-hard vertex-cover (VC) combinatorial optimization problem is studied numerically by linear programming (LP) on ensembles of random graphs. As the basic Simplex (SX) algorithm suitable for such LPs may produce incomplete solutions for sufficiently complex graphs, the application of cutting-plane (CP) methods is sought.

Lothar Schiemanowski

A natural approach to the construction of nearly G2 manifolds lies in resolving nearly G2 spaces with isolated conical singularities by gluing in asymptotically conical G2 manifolds modelled on the same cone. If such a resolution exits, one expects there to be a family of nearly G2 manifolds, whose endpoint is the original nearly G2 conifold and whose parame

Ilya Osadchiy, Kfir Y. Levy, Ron Meir

We study meta-learning for adversarial multi-armed bandits. We consider the online-within-online setup, in which a player (learner) encounters a sequence of multi-armed bandit episodes. The player's performance is measured as regret against the best arm in each episode, according to the losses generated by an adversary. The difficulty of the problem depends

Stefan Steinerberger

Let $x_1, \dots, x_n$ be points in a metric space and define the distance matrix $D \in \mathbb{R}^{n \times n}$ by ${D}_{ij} = d(x_i, x_j)$. The Perron-Frobenius Theorem implies that there is an eigenvector $v \in \mathbb{R}^n_{}$ with non-negative entries associated to the largest eigenvalue. We prove that this eigenvector is nearly constant in the sense t

Hardi Peter, Lakshmi Pradeep Chitta, Feng Chen, David I. Pontin

The outer atmosphere of the Sun is composed of plasma heated to temperatures well in excess of the visible surface. We investigate short cool and warm (<1 MK) loops seen in the core of an active region to address the role of field-line braiding in energising these structures. We report observations from the High-resolution Coronal imager (Hi-C) that have bee

Pierre Erbacher, Ludovic Denoyer, Laure Soulier

When users initiate search sessions, their queries are often unclear or might lack of context; this resulting in inefficient document ranking. Multiple approaches have been proposed by the Information Retrieval community to add context and retrieve documents aligned with users' intents. While some work focus on query disambiguation using users' browsing hist

Cristina Matache, Sean Moss, Sam Staton

We study concrete sheaf models for a call-by-value higher-order language with recursion. Our family of sheaf models is a generalization of many examples from the literature, such as models for probabilistic and differentiable programming, and fully abstract logical relations models. We treat recursion in the spirit of synthetic domain theory. We provide a ge

Roger A. Hegstrom, Alexandra J. MacDermott

Several recent studies have suggested that incompatible variables, which play an essential role in quantum mechanics (QM), are, somewhat surprisingly, not necessarily unique to QM. To investigate this possibility and obtain a better understanding of two central postulates of QM, namely the commutator postulate and the Born postulate, we introduce a classical

Jincheng Guo, Cheng Liu

Recently, a single-line spectroscopic binary, LTD064402+245919, has been discovered by Yang et al. Using data from LAMOST and ZTF, the unseen companion is estimated to have a mass of 1-3 $M_{\odot}$, orbiting a subgiant with orbital period of 14.50 days, making it a good compact binary candidate without X-ray emission. However, new light curves from ZTF and

Lorenzo Ceragioli, Letterio Galletta, Pierpaolo Degano, David Basin

Security Enhanced Linux (SELinux) is a security architecture for Linux implementing mandatory access control. It has been used in numerous security-critical contexts ranging from servers to mobile devices. But this is challenging as SELinux security policies are difficult to write, understand, and maintain. Recently, the intermediate language CIL was introdu

R. Abou Yassine, J. Adamczewski-Musch, O. Arnold, E. T. Atomssa

First information on the time-like electromagnetic structure of baryons in the second resonance region has been obtained from measurements of dielectron (e+ e-) invariant-mass and angular distributions in the quasi-free reaction $\pi-$ p $\rightarrow$ n e+ e- at $\sqrt{s_{\pi p}}$ = 1.49 GeV with the High Acceptance Di-Electron Spectrometer (HADES) at GSI us

Van Truong Hoang, Manh Duong Phung

This paper introduces a new path planning algorithm for unmanned aerial vehicles (UAVs) based on the teaching-learning-based optimization (TLBO) technique. We first define an objective function that incorporates requirements on the path length and constraints on the movement and safe operation of UAVs to convert the path planning into an optimization problem

Jishnu Roychoudhury, Jatin Yadav

Sorting is a foundational problem in computer science that is typically employed on sequences or total orders. More recently, a more general form of sorting on partially ordered sets (or posets), where some pairs of elements are incomparable, has been studied. General poset sorting algorithms have a lower-bound query complexity of $\Omega(wn + n \log n)$, wh

Onur Oktay

We inspect the properties of reflexive Banach algebras that are related to the pointwise products of its weakly null sequences.

Fabio Silva Botelho

This article develops an approximate proximal approach for the generalized method of lines. The present results are extensions and applications of previous ones which have been published since 2011, in books and articles such as [3,4,5,6]. We also recall that in the generalized method of lines, the domain of the partial differential equation in question is d

Pedro M. Gordaliza

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb.) that produces pulmonary damage due to its airborne nature. This fact facilitates the disease fast-spreading, which, according to the World Health Organization (WHO), in 2021 caused 1.2 million deaths and 9.9 million new cases. Fortunately, X-Ray Computed Tomography (CT) im

Yashveer Kuma, Somveer Singh, Reshma Singh, Vineet Kumar Singh

This article provides an effective computational algorithm based on Legendre wavelet (LW) and standard tau approach to approximate the solution of multi-dimensional distributed order time-space fractional weakly singular integro-partial differential equation (DOT-SFWSIPDE). To the best of our understanding, the proposed computational algorithm is new and has

Gabriele Nebe

An ordinary character $\chi $ of a finite group is called orthogonally stable, if all non-degenerate invariant quadratic forms on any module affording the character $\chi $ have the same discriminant. This is the orthogonal discriminant, $\disc(\chi )$, of $\chi $, a square class of the character field. Based on experimental evidence we conjecture that the o

Malsha V. Perera, Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu, Vishal M. Patel

Synthetic Aperture Radar (SAR) despeckling is an important problem in remote sensing as speckle degrades SAR images, affecting downstream tasks like detection and segmentation. Recent studies show that convolutional neural networks(CNNs) outperform classical despeckling methods. Traditional CNNs try to increase the receptive field size as the network goes de

Yang Shen, Bin Zou

We consider monotone mean-variance (MMV) portfolio selection problems with a conic convex constraint under diffusion models, and their counterpart problems under mean-variance (MV) preferences. We obtain the precommitted optimal strategies to both problems in closed form and find that they coincide, without and with the presence of the conic constraint. This

Jörn Kuhlenkamp, Sebastian Werner, Chin Hong Tran, Stefan Tai

A proper configuration of an information system can ensure accuracy and efficiency, among other system objectives. Conversely, a poor configuration can have a significant negative impact on the system's performance, reliability, and cost. Serverless systems, which are comprised of many functions and managed services, especially risk exposure to misconfigurat

Valerio Marsocci, Virginia Coletta, Roberta Ravanelli, Simone Scardapane

Change detection is one of the most active research areas in Remote Sensing (RS). Most of the recently developed change detection methods are based on deep learning (DL) algorithms. This kind of algorithms is generally focused on generating two-dimensional (2D) change maps, thus only identifying planimetric changes in land use/land cover (LULC) and not consi

Marc Lambert, Sinho Chewi, Francis Bach, Silvère Bonnabel

Along with Markov chain Monte Carlo (MCMC) methods, variational inference (VI) has emerged as a central computational approach to large-scale Bayesian inference. Rather than sampling from the true posterior $\pi$, VI aims at producing a simple but effective approximation $\hat \pi$ to $\pi$ for which summary statistics are easy to compute. However, unlike th

Hang Du, Yifan Gao, Xinyi Li, Zijie Zhuang

In this work, we consider critical planar site percolation on the triangular lattice and derive sharp estimates on the asymptotics of the probability of half-plane $j$-arm events for $j \geq 1$ and planar (polychromatic) $j$-arm events for $j>1$. These estimates greatly improve previous results and in particular answer (a large part of) a question of Schramm

V. Bertone, G. Bozzi, F. Hautmann

We discuss perturbative solutions of renormalization group equations, and propose the use of resummation scale techniques in assessing theoretical uncertainties on the extraction of parton distribution functions from data.

Nguyen N. Hung

Let $p$ be a prime and $G$ a finite group. We propose a strong bound for the number of $p'$-degree irreducible characters of $G$ in terms of the commutator factor group of a Sylow $p$-subgroup of $G$. The bound arises from a recent conjecture of Navarro and Tiep [NT21] on fields of character values and a phenomenon called the continuity of $p$-rationality le

Ghiles Reguig, Marie Chupin, Hugo Dary, Eric Bardinet

Due to the growing number of MRI data, automated quality control (QC) has become essential, especially for larger scale analysis. Several attempts have been made in order to develop reliable and scalable QC pipelines. However, the generalization of these methods on new data independent of those used for learning is a difficult problem because of the biases i

Neal Hermer, D. Russell Luke, Anja Sturm

We study the convergence of random function iterations for finding an invariant measure of the corresponding Markov operator. We call the problem of finding such an invariant measure the stochastic fixed point problem. This generalizes earlier work studying the stochastic feasibility problem, namely, to find points that are, with probability 1, fixed points

Qiying Pan, Yifei Zhu

Node embedding aims to map nodes in the complex graph into low-dimensional representations. The real-world large-scale graphs and difficulties of labeling motivate wide studies of unsupervised node embedding problems. Nevertheless, previous effort mostly operates in a centralized setting where a complete graph is given. With the growing awareness of data pri

Bangwei Guo, Xingyu Li, Miaomiao Yang, Hong Zhang

Deep-learning models based on whole-slide digital pathology images (WSIs) become increasingly popular for predicting molecular biomarkers. Instance-based models has been the mainstream strategy for predicting genetic alterations using WSIs although bag-based models along with self-attention mechanism-based algorithms have been proposed for other digital path

Dimitrios Mallis, Enrique Sanchez, Matt Bell, Georgios Tzimiropoulos

This paper proposes a novel paradigm for the unsupervised learning of object landmark detectors. Contrary to existing methods that build on auxiliary tasks such as image generation or equivariance, we propose a self-training approach where, departing from generic keypoints, a landmark detector and descriptor is trained to improve itself, tuning the keypoints

Kashif Rasul, Young-Jin Park, Max Nihlén Ramström, Kyung-Min Kim

Time series models aim for accurate predictions of the future given the past, where the forecasts are used for important downstream tasks like business decision making. In practice, deep learning based time series models come in many forms, but at a high level learn some continuous representation of the past and use it to output point or probabilistic foreca

Adamantia Zampeli, Georgios E. Pavlou, Petros Wallden

In the histories formulation of quantum theory, sets of coarse-grained histories that are consistent obey the classical probability rules. It has been argued that these sets can describe the quasi-classical behaviour of closed quantum systems, e.g. Omnes (Rev. Mod. Phys. 64(2), 339, 1992) and Hartle (Les Houches1992). Most physical scenarios admit multiple d

A. Quinn, M. Brown, T. J. Gardner, D. T. C. Allcock

The majority of microfabricated ion traps in use for quantum information processing are of the 2D 'surface-electrode' type or of the 3D 'wafer' type. Surface-electrode traps greatly simplify fabrication and hold the promise of allowing trapped-ion quantum computers to scale via standard semiconductor industry fabrication techniques. However, their geometry c

Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar

Although parallelism has been extensively used in reinforcement learning (RL), the quantitative effects of parallel exploration are not well understood theoretically. We study the benefits of simple parallel exploration for reward-free RL in linear Markov decision processes (MDPs) and two-player zero-sum Markov games (MGs). In contrast to the existing litera

Michael de Oliveira, Marco Piccardo, Sahand Eslami, Vincenzo Aglieri

To exploit the full potential of the transverse spatial structure of light using the Laguerre-Gaussian basis, it is necessary to control the azimuthal and radial components of the photons. Vortex phase elements are commonly used to generate these modes of light, offering precise control over the azimuthal index but neglect the radially dependent amplitude te

Amar Aryan, Shashi Bhushan Pandey, Abhay Pratap Yadav, Amit Kumar

In this work, we study the synthetic explosions of a massive star. We take a 100 M$_{\odot}$ zero--age main--sequence (ZAMS) star and evolve it until the onset of core-collapse using {\tt MESA}. Then, the resulting star model is exploded using the publicly available stellar explosion code, {\tt STELLA}. The outputs of {\tt STELLA} calculations provide us the

Amar Aryan, Shashi Bhushan Pandey, Amit Kumar, Rahul Gupta

In this work, we employ two publicly available analysis tools to study four hydrogen(H)--stripped core--collapse supernovae (CCSNe) namely, SN 2009jf, iPTF13bvn, SN 2015ap, and SN 2016bau. We use the Modular Open-Source Fitter for Transients ({\tt MOSFiT}) to model the multi band light curves. {\tt MOSFiT} analyses show ejecta masses (log M$_{ej}$) of $0.80_

David Jaz Myers

Informally, an orbifold is a smooth space whose points may have finitely many internal symmetries. Formally, however, the notion of orbifold has been presented in a number of different guises -- from Satake's V-manifolds to Moerdijk and Pronk's proper \'etale groupoids -- which do not on their face resemble the informal definition. The reason for this diverg

Yan-cheng Li, Sai Peng, Taiba Kouser

A numerical study of two-dimensional flow past a confined circular cylinder with slip wall is performed. A dimensionless number, Knudsen number ($Kn$) is used to describe the slip length of cylinder wall. The Reynolds number ($Re$) and Knudsen number ($Kn$) ranges considered are $Re = [1, 180]$ and $Kn = [0, \infty)$, respectively. Time-averaged flow separat

Ian Bell, Robin Fingerhut, Jadran Vrabec, Lorenzo Costigliola

It is shown that the residual entropy (entropy minus that of the ideal gas at the same temperature and density) is mostly synonymous with the independent variable of density scaling, identifying a direct link between these two approaches. The two-body residual entropy is demonstrated to not be a suitable surrogate for the total residual entropy in the gas ph

Yani Xue, Miqing Li, Xiaohui Liu

In evolutionary multiobjective optimization, effectiveness refers to how an evolutionary algorithm performs in terms of converging its solutions into the Pareto front and also diversifying them over the front. This is not an easy job, particularly for optimization problems with more than three objectives, dubbed many-objective optimization problems. In such

Tanusree Saha, Luca Petaccia, Barbara Ressel, Primož Rebernik Ribič

We present an angle-resolved photoemission study of the electronic band structure of the excitonic insulator Ta$_2$NiSe$_5$, as well as its evolution upon Sulfur doping. Our experimental data show that while the excitonic insulating phase is still preserved at a Sulfur-doping level of 25$\%$, such phase is heavily suppressed when there is a substantial amoun

João Machado de Freitas, Sebastian Berg, Bernhard C. Geiger, Manfred Mücke

In this paper, we frame homogeneous-feature multi-task learning (MTL) as a hierarchical representation learning problem, with one task-agnostic and multiple task-specific latent representations. Drawing inspiration from the information bottleneck principle and assuming an additive independent noise model between the task-agnostic and task-specific latent rep

Robin Stoll

We study versions of Goodwillie's calculus of functors for indexing diagrams other than cubes. We in particular construct universal excisive approximations for a larger class of diagrams, which yields an extension of the Taylor tower. We prove that the limit of this extension agrees with the limit of the Taylor tower using criteria for the existence of maps

Siqi Liu, Marc Lanctot, Luke Marris, Nicolas Heess

Learning to play optimally against any mixture over a diverse set of strategies is of important practical interests in competitive games. In this paper, we propose simplex-NeuPL that satisfies two desiderata simultaneously: i) learning a population of strategically diverse basis policies, represented by a single conditional network; ii) using the same networ

Josu C. Aurrekoetxea, Pedro G. Ferreira, Katy Clough, Eugene A. Lim

We study the generation and propagation of gravitational waves in scalar-tensor gravity using numerical relativity simulations of scalar field collapses beyond spherical symmetry. This allows us to compare the tensor and additional massive scalar waves that are excited. As shown in previous work in spherical symmetry, massive propagating scalar waves decay f

Tristan Phillips

In this note we give exact formulas (and asymptotics) for the number of rational points of bounded height on weighted projective stacks over global function fields.

Helge Kristian Jenssen, Alexander Anthony Johnson

We consider self-similar solutions to the full compressible Euler system for an ideal gas in two and three space dimensions. The system admits a 2-parameter family of similarity solutions depending on parameters $\lambda$ and $\kappa$. Requiring locally finite amounts of mass, momentum, and energy imply certain constraints on $\lambda$ and $\kappa$. Further

Iris A. M. Huijben, Arthur A. Nijdam, Sebastiaan Overeem, Merel M. van Gilst

Continuous monitoring with an ever-increasing number of sensors has become ubiquitous across many application domains. However, acquired time series are typically high-dimensional and difficult to interpret. Expressive deep learning (DL) models have gained popularity for dimensionality reduction, but the resulting latent space often remains difficult to inte

Benjamin Qi

We study the problem of Regularized Unconstrained Submodular Maximization (RegularizedUSM) as defined by Bodek and Feldman [BF22]. In this problem, you are given a non-monotone non-negative submodular function $f:2^{\mathcal N}\to \mathbb R_{\ge 0}$ and a linear function $\ell:2^{\mathcal N}\to \mathbb R$ over the same ground set $\mathcal N$, and the object

F. Hautmann, M. Hentschinski, L. Keersmaekers, A. Kusina

Off-shell, transverse-momentum dependent splitting functions can be defined from the high-energy limit of partonic decay amplitudes. Based on these splitting functions, we construct Sudakov form factors and formulate a new parton branching algorithm. We present a first Monte Carlo implementation of the algorithm. We use the numerical results to verify explic

C. Glaser, S. McAleer, S. Stjärnholm, P. Baldi

Ultra-high-energy (UHE) neutrinos ($>10^{16}$ eV) can be measured cost-effectively using in-ice radio detection, which has been explored successfully in pilot arrays. A large radio detector is currently being constructed in Greenland with the potential to measure the first UHE neutrino, and an order-of-magnitude more sensitive detector is being planned with

Frederik Møller, Sebastian Erne, Norbert J. Mauser, Jörg Schmiedmayer

Generalized Hydrodynamics (GHD) has recently been devised as a method to solve the dynamics of integrable quantum many-body systems beyond the mean-field approximation. In its original form, a major limitation is the inability to predict equal-time correlations. Here we present a new method to treat thermal fluctuations of a 1D bosonic degenerate gas within

Ludwig A. Hothorn

Standard ANOVA is among the most widely used tests in the life sciences and beyond. Several alternatives are proposed to provide simultaneous confidence intervals, ensure tight control of FWER, be robust to variance heterogeneity, avoid pre-testing for global effect (for one-way designs) or irrelevant interaction (for multi-way designs) prior to multiple com

Mostafa Elhashash, Hessah Albanwan, Rongjun Qin

The evolution of mobile mapping systems (MMSs) has gained more attention in the past few decades. MMSs have been widely used to provide valuable assets in different applications. This has been facilitated by the wide availability of low-cost sensors, the advances in computational resources, the maturity of the mapping algorithms, and the need for accurate an

Nicolas Billerey, Imin Chen, Luis Dieulefait, Nuno Freitas

In 2000, Darmon described a program to study the generalized Fermat equation using modularity of abelian varieties of $\mathrm{GL}_2$-type over totally real fields. The original approach was based on hard open conjectures, which have made it difficult to apply in practice. In this paper, building on the progress surrounding the modular method from the last t

Ibrahim Alabdulmohsin, Jessica Schrouff, Oluwasanmi Koyejo

We propose a novel reduction-to-binary (R2B) approach that enforces demographic parity for multiclass classification with non-binary sensitive attributes via a reduction to a sequence of binary debiasing tasks. We prove that R2B satisfies optimality and bias guarantees and demonstrate empirically that it can lead to an improvement over two baselines: (1) tre

Ziyi Liu, Xian Guo, Yongchun Fang

While various multi-agent reinforcement learning methods have been proposed in cooperative settings, few works investigate how self-interested learning agents achieve mutual coordination in decentralized general-sum games and generalize pre-trained policies to non-cooperative opponents during execution. In this paper, we present Generalizable Risk-Sensitive

Afshin Shoeibi, Navid Ghassemi, Marjane Khodatars, Parisa Moridian

Nowadays, many people worldwide suffer from brain disorders, and their health is in danger. So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and attention deficit hyperactivity disorder (ADHD), among which functional magnetic resonance imaging (fMRI) modalities are known as a popular method among physicians. This paper pres

Florentin Münch

We give a discrete Bonnet Myers type theorem for the effective diameter assuming positive Ollivier curvature. We prove that this diameter bound is attained if and only if the graph is a cocktail party graph, a Johnson graph, a halved cube, a Schl\"afli graph, a Gosset graph, or a cartesian product of the mentioned graphs with same Ollivier curvature. As a ke

Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro

Graph neural networks (GNN) are an effective framework that exploit inter-relationships within graph-structured data for learning. Principal component analysis (PCA) involves the projection of data on the eigenspace of the covariance matrix and draws similarities with the graph convolutional filters in GNNs. Motivated by this observation, we study a GNN arch

Ganlin Lyu, Chao Chen, Xi Du, Shahid Mughal

We introduce an open-source and unified framework for transition analysis for laminar boundary layer natural transition at transonic conditions and over complex geometries, where surface irregularities may be present. Different computational tools are integrated in the framework, and therefore overcomes the difficulties of two separate and usually quite disp

Markus Vaefeni Hitila, Sylvanus Ameh Onjefu

Primordial radionuclides such as uranium (U-238), thorium (Th-232), and potassium (K-40) and their progenies contained in coal can be a source of concern to the environment in a thermal coal-powered plant. In this study, the average activity concentrations of Ra-226, Th-232, and K-40 in the soil around the Van Eck coal-fired power plant in Namibia were deter